Mental Imagery for Intelligent Vehicles

Alice Plebe, Riccardo Donà, Gastone Pietro Papini Rosati, Mauro Da Lio

Abstract

The research in the design of self-driving vehicles has been boosted, in the last decades, by the developments in the fields of artificial intelligence. Despite the growing number of industrial and research initiatives aimed at implementing autonomous driving, none of them can claim, yet, to have reached the same driving performance of a human driver. In this paper, we will try to build upon the reasons why the human brain is so effective in learning tasks as complex as the one of driving, borrowing explanations from the most established theories on sensorimotor learning in the field of cognitive neuroscience. The contribution of this work would like to be a new point of view on how the known capabilities of the brain can be taken as an inspiration for the implementation of a more robust artificial driving agent. In this direction, we consider the Convergence-divergence Zones (CDZs) as the most prominent proposal in explaining the simulation process underlying the human sensorimotor learning. We propose to use the CDZs as a “template” for the implementation of neural network models mimicking the phenomenon of mental imagery, which is considered to be at the heart of the human ability to perform sophisticated sensorimotor controls such driving.

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Paper Citation


in Harvard Style

Plebe A., Donà R., Papini Rosati G. and Da Lio M. (2019). Mental Imagery for Intelligent Vehicles.In Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-374-2, pages 43-51. DOI: 10.5220/0007657500430051


in Bibtex Style

@conference{vehits19,
author={Alice Plebe and Riccardo Donà and Gastone Pietro Papini Rosati and Mauro Da Lio},
title={Mental Imagery for Intelligent Vehicles},
booktitle={Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2019},
pages={43-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007657500430051},
isbn={978-989-758-374-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Mental Imagery for Intelligent Vehicles
SN - 978-989-758-374-2
AU - Plebe A.
AU - Donà R.
AU - Papini Rosati G.
AU - Da Lio M.
PY - 2019
SP - 43
EP - 51
DO - 10.5220/0007657500430051